Population Density (people per sq km of land area) by block group in the State of Iowa based on U.S. Census Bureau, 2013-2017 American Community Survey 5-Year Estimates. Used in the Transit Dependency Analysis as part of the 2020 Iowa DOT Public Transit Long Range Plan update. This factor was one of seven utilized in the analysis that was based on MTI Report 12-30 "Investigating the Determining Factors for Transit Travel Demand by Bus Mode in US Metropolitan Statistical Areas" by the Mineta Transportation Institute of San José State University (SJSU) in May 2015.More information on the Transit Dependency Analysis can be found in Appendix 2 of the Iowa Public Transit Long Range Plan.

The 2015 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2010.

The feature class contains the current urban area boundaries for the State of Iowa. An urban area will comprise a densely settled core of census tracts and/or census blocks that meet minimum population density requirements, along with adjacent territory containing non-residential urban land uses as well as territory with low population density included to link outlying densely settled territory with the densely settled core. To qualify as an urban area, the territory identified according to criteria must encompass at least 2,500 people, at least 1,500 of which reside outside institutional group quarters.

Composite of transit ridership dependency factor median values across all transit agency sizes, generated using the 'Weighted Overlay' geoprocessing tool and set to equal influence for all factors, resulting in a non-weighted composite overlay as part of the Iowa Public Transit Long Range Plan conducted in 2020. Each of the seven factors (gas prices, household income, carless households, language, race, college enrollment, population density) were evaluated equally as it pertains to how much each factor impacts transit dependency.More information on the Transit Dependency Analysis can be found in Appendix 2 of the Iowa Public Transit Long Range Plan.

This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Iowa. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Iowa. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment units. In this data set, these variables are linked to the catchments of the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. They can also be linked to the reaches of the NHDPlusV1 using the COMID identifier. Catchment attributes are available for both local catchments (defined as the land area draining directly to a reach; attributes begin with "L_" prefix) and network catchments (defined by all upstream contributing catchments to the reach's outlet, including the reach's own local catchment; attributes begin with "N_" prefix). This shapefile also includes habitat condition scores created based on responsiveness of biological metrics to anthropogenic landscape disturbances throughout ecoregions. Separate scores were created by considering disturbances within local catchments, network catchments, and a cumulative score that accounted for the most limiting disturbance operating on a given biological metric in either local or network catchments. This assessment only scored reaches representing streams and rivers (see the process section for more details). Please use the following citation: Esselman, P., D.M. Infante, L. Wang, W. Taylor, W. Daniel, R. Tingley, J. Fenner, A. Cooper, D. Wieferich, D. Thornbrugh and J. Ross. (April 2011) National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Iowa. National Fish Habitat Partnership Data System. http://dx.doi.org/doi:10.5066/F7CR5RCJ

Composite of transit ridership dependency factor median values across all transit agency sizes, generated using the 'Weighted Overlay' geoprocessing tool and set to equal influence for all factors, resulting in a non-weighted composite overlay or using a '1 to 10 by 1' evaluation scale based on percentage values provided by participating transit agencies in the State of Iowa as part of the Iowa Public Transit Long Range Plan conducted in 2020. Each of the seven factors (gas prices, household income, carless households, language, race, college enrollment, population density) were evaluated equally as it pertains to how much each factor impacts transit dependency for the non-weighted composite overlay. Weighted scores from four large urban transit agencies (Des Moines Area Regional Transit, Iowa City Transit, University of Iowa CamBus, Sioux City Transit, Bettendorf Transit), three small urban transit agencies (Mason City Transit, Marshalltown Transit, Muscatine Transit), and seven regional transit agencies (Southern Iowa Trolley, ECICOG, INRCOG, SWIPCO, River Bend Transit, SIMPCO) were utilized in the generation of the weighted composite overlays.More information on the Transit Dependency Analysis can be found in Appendix 2 of the Iowa Public Transit Long Range Plan.

Beta coefficients (with standard errors) on the logit scale included in the most competitive models for breeding marsh birds surveyed at shallow lakes in the Prairie Pothole Region of Iowa, summer 2016 and 2017.

Restored shallow lakes are indicated by an asterisk. (XLSX)

Model selection results for detection probability for seven species of breeding marsh birds surveyed at shallow lakes in the Prairie Pothole Region of Iowa, summer 2016 and 2017.

The 2019 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are as of January 1, 2010.

The Marsh Ecology Research Program (MERP) was a long-term interdisciplinary study on the ecology of prairie wetlands. A scientific team from a variety of disciplines (hydrology, plant ecology, invertebrate ecology, vertebrate ecology, nutrient dynamics, marsh management) was assembled to design and oversee a long-term experiment on the effects of water-level manipulation on northern prairie wetlands. Ten years of fieldwork (1980 -1989), combining a routine long-term monitoring program and a series of short-term studies, generated a wealth of new and diverse information on the ecology and function of prairie wetlands (Murkin, Batt, Caldwell, Kadlec and van der Valk, 2000). This data set includes muskrat population data, collected as part of the vertebrate monitoring program of MERP. Re-colonizing muskrat (Ondatra zibethicus) populations in the MERP experimental cells were monitored during the 1985-1989 sampling seasons to explore the effects water level and associated vegetation characteristics had on muskrat density, population size, habitat use, body condition, and survival and reproductive rates (Clark and Murkin, 1989).

For further information on the Marsh Ecology Research Program (MERP), please visit: http://www.ducks.ca/conserve/research/projects/merp/index.html

References: Clark, W.R., and H.R. Murkin. 1989. Vertebrates. In: Marsh Ecology Research Program: Long-term Monitoring Procedures Manual. (Eds.) E.J. Murkin and H.R. Murkin, pp. 35-38. Manitoba, Canada: Delta Waterfowl and Wetlands Research Station. Murkin, H.R., B.D.J. Batt, P.J. Caldwell, J.A. Kadlec and A.G. van der Valk. 2000a. Introduction to the Marsh Ecology Research Program. In Prairie Wetland Ecology: The Contribution of the Marsh Ecology Research Program. (Eds) H.R. Murkin, A.G. van der Valk and W.R. Clark. pp. 3-15. Ames: Iowa State University Press.

Resulting Publications on Muskrat Populations Clark., W.R. 1990. Compensation in furbearer populations; current data compared with a review of concepts. Transactions of the North American Wildlife and Natural resources Conference 55: 491-500. Clark, W.R. 1994. Habitat selection by muskrats in experimental marshes undergoing succession. Canadian Journal of Zoology 72: 675-680. Clark, W.R., and D.W. Kroeker. 1993. Population dynamics of muskrats in managed marshes at Delta, Manitoba. Canadian Journal of Zoology 71: 1620-1628. Clark, W.R. 2000. Ecology of muskrats in prairie wetlands. In Prairie Wetland Ecology: The Contribution of the Marsh Ecology Research Program. (Eds.) H.R. Murkin, A.G. van der Valk, and W.R. Clark, pp. 37-54. Iowa: Iowa State University Press.